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提交 c066b30a authored 作者: Pascal Lamblin's avatar Pascal Lamblin
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PEP 8

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theano/compile/mode.py
浏览文件 @ c066b30a
"""WRITEME
"""
import os, logging, warnings
import logging
import numpy, theano
import numpy
import theano
from theano import gof
import theano.gof.vm
from theano.configparser import config, AddConfigVar, StrParam, EnumStr
from theano.configparser import config, AddConfigVar, StrParam
_logger = logging.getLogger('theano.compile.mode')
AddConfigVar('optimizer_excluding',
"When using the default mode, we will remove optimizer with that tag. Separate many tags with ':'.",
("When using the default mode, we will remove optimizer with these "
"tags. Separate tags with ':'."),
StrParam("", allow_override=False),
in_c_key=False)
AddConfigVar('optimizer_including',
"When using the default mode, we will add optimizer with that tag. Separate many tags with ':'.",
("When using the default mode, we will add optimizer with these tags. "
"Separate tags with ':'."),
StrParam("", allow_override=False),
in_c_key=False)
AddConfigVar('optimizer_requiring',
"When using the default mode, we will require optimizer with that tag. Separate many tags with ':'.",
("When using the default mode, we will require optimizer with these "
"tags. Separate tags with ':'."),
StrParam("", allow_override=False),
in_c_key=False)
def check_equal(x, y):
"""
Returns True iff x[0] and y[0] are equal (checks the dtype and
......@@ -32,35 +38,37 @@ def check_equal(x, y):
import scipy.sparse as sp
x, y = x[0], y[0]
# TODO: bug in current scipy, two sparse matrices are never equal, remove when moving to 0.7
# TODO: bug in current scipy, two sparse matrices are never equal,
# remove when moving to 0.7
if sp.issparse(x):
x = x.todense()
if sp.issparse(y):
y = y.todense()
if isinstance(x, numpy.ndarray) and isinstance(y, numpy.ndarray):
if x.dtype != y.dtype or x.shape != y.shape or numpy.any(abs(x - y) > 1e-10):
raise Exception("Output mismatch.", {'performlinker': x, 'clinker': y})
if (x.dtype != y.dtype
or x.shape != y.shape
or numpy.any(abs(x - y) > 1e-10)):
raise Exception("Output mismatch.",
{'performlinker': x, 'clinker': y})
else:
if x != y:
raise Exception("Output mismatch.", {'performlinker': x, 'clinker': y})
raise Exception("Output mismatch.",
{'performlinker': x, 'clinker': y})
# If a string is passed as the linker argument in the constructor for
# Mode, it will be used as the key to retrieve the real linker in this
# dictionary
predefined_linkers = {
'py' : gof.PerformLinker(),
'c' : gof.CLinker(),
'c|py' : gof.OpWiseCLinker(allow_gc=True),
'c|py_nogc' : gof.OpWiseCLinker(allow_gc=False),
'c&py' : gof.DualLinker(checker = check_equal),
'vm' : gof.vm.VM_Linker(allow_gc=True, use_cloop=False),
'cvm' : gof.vm.VM_Linker(allow_gc=True, use_cloop=True),
'vm_nogc' : gof.vm.VM_Linker(allow_gc=False, use_cloop=False),
'py': gof.PerformLinker(),
'c': gof.CLinker(),
'c|py': gof.OpWiseCLinker(allow_gc=True),
'c|py_nogc': gof.OpWiseCLinker(allow_gc=False),
'c&py': gof.DualLinker(checker=check_equal),
'vm': gof.vm.VM_Linker(allow_gc=True, use_cloop=False),
'cvm': gof.vm.VM_Linker(allow_gc=True, use_cloop=True),
'vm_nogc': gof.vm.VM_Linker(allow_gc=False, use_cloop=False),
'cvm_nogc': gof.vm.VM_Linker(allow_gc=False, use_cloop=True),
}
......@@ -72,37 +80,37 @@ def register_linker(name, linker):
predefined_linkers[name] = linker
# If a string is passed as the optimizer argument in the constructor
# for Mode, it will be used as the key to retrieve the real optimizer
# in this dictionary
OPT_FAST_RUN = gof.Query(include = ['fast_run'])
OPT_FAST_RUN = gof.Query(include=['fast_run'])
OPT_FAST_RUN_STABLE = OPT_FAST_RUN.requiring('stable')
OPT_FAST_COMPILE = gof.Query(include = ['fast_compile'])
OPT_STABILIZE = gof.Query(include = ['fast_run'])
OPT_FAST_COMPILE = gof.Query(include=['fast_compile'])
OPT_STABILIZE = gof.Query(include=['fast_run'])
OPT_STABILIZE.position_cutoff = 1.5000001
predefined_optimizers = {
None : lambda env: None,
'None' : lambda env: None,
'merge' : gof.MergeOptimizer(),
'fast_run' : OPT_FAST_RUN,
'fast_run_stable' : OPT_FAST_RUN_STABLE,
'fast_compile' : OPT_FAST_COMPILE,
None: (lambda env: None),
'None': (lambda env: None),
'merge': gof.MergeOptimizer(),
'fast_run': OPT_FAST_RUN,
'fast_run_stable': OPT_FAST_RUN_STABLE,
'fast_compile': OPT_FAST_COMPILE,
'stabilize': OPT_STABILIZE
}
def register_optimizer(name, opt):
"""Add a `Optimizer` which can be referred to by `name` in `Mode`."""
if name in predefined_optimizers:
raise ValueError('Optimizer name already taken: %s' % name)
predefined_optimizers[name] = opt
def register_OutputGuard_c_code(type):
OutputGuard.c_code_types.append(type)
class OutputGuard(gof.Op):
"""
This op is used only internally by Theano.
......@@ -120,20 +128,24 @@ class OutputGuard(gof.Op):
TODO: find a current full explanation.
"""
destroy_map = {0:[0]}
view_map = {0:[0]}
destroy_map = {0: [0]}
view_map = {0: [0]}
c_code_types = []
def make_node(self, x):
return gof.Apply(self, [x], [x.type()])
def __eq__(self, other):
return type(self) == type(other)
def __hash__(self):
return hash(type(self))
def perform(self, node, inp, out):
x, = inp
z, = out
z[0] = x
def __str__(self):
return '%s' % self.__class__.__name__
......@@ -141,7 +153,8 @@ class OutputGuard(gof.Op):
x, = inp
z, = out
if isinstance(node.inputs[0].type, theano.scalar.Scalar):
# Scalars are C objects on the stacks, and should not be inc/decrefed
# Scalars are C objects on the stack,
# and should not be inc/decrefed
return """
%(z)s = %(x)s;
""" % locals()
......@@ -161,71 +174,99 @@ class OutputGuard(gof.Op):
_output_guard = OutputGuard()
class AddDestroyHandler(gof.Optimizer):
"""This optimizer performs two important functions:
1) it has a 'requirement' of the destroyhandler. This means that the env will include it
as a feature for this optimization, and keep this feature enabled for subsequent
optimizations. All optimizations that work inplace on any of their inputs must run *after*
this optimization to ensure that the DestroyHandler has been included in the env.
1) it has a 'requirement' of the destroyhandler. This means that the env
will include it as a feature for this optimization, and keep this feature
enabled for subsequent optimizations. All optimizations that work inplace
on any of their inputs must run *after* this optimization to ensure that
the DestroyHandler has been included in the env.
2) It tries to replace each output with an Op that purports to destroy it (but it won't I
promise). If this replacement succeeds it means that there is a bug in theano. It should
not be possible to destroy outputs.
2) It tries to replace each output with an Op that purports to destroy it
(but it won't I promise). If this replacement succeeds it means that
there is a bug in theano. It should not be possible to destroy outputs.
"""
def apply(self, env):
for o in env.outputs:
try:
env.replace_validate(o, _output_guard(o), reason='output_guard')
_logger.info("Output variable %s required output_guard,"
" how was this output left unprotected against destructive operations?"
env.replace_validate(o, _output_guard(o),
reason='output_guard')
_logger.info("Output variable %s required output_guard, "
"how was this output left unprotected against "
"destructive operations?"
% o)
except gof.InconsistencyError:
#this output is already impossible to destroy. no guard necessary
# This output is already impossible to destroy.
# No guard necessary
pass
def add_requirements(self, env):
super(AddDestroyHandler, self).add_requirements(env)
env.extend(gof.DestroyHandler())
class PrintCurrentEnv(gof.Optimizer):
"""This optimizer is for debugging.
Toss it into the optimization pipeline to see the state of things at any given point.
Toss it into the optimization pipeline to see the state of things at any
given point.
"""
def __init__(self, header):
self.header =header
self.header = header
def apply(self, env):
import theano.printing
print "PrintCurrentEnv:", self.header
theano.printing.debugprint(env.outputs)
optdb = gof.SequenceDB()
optdb.register('merge1', gof.MergeOptimizer(),
0, 'fast_run', 'fast_compile')
optdb.register('canonicalize', gof.EquilibriumDB(), # rearranges elemwise expressions
# rearranges elemwise expressions
optdb.register('canonicalize', gof.EquilibriumDB(),
1, 'fast_run', 'fast_compile')
optdb.register('merge1.2', gof.MergeOptimizer(),
1.2, 'fast_run', 'fast_compile')
optdb.register('Print1.21', PrintCurrentEnv('Post-canonicalize'),
1.21,)# 'fast_run', 'fast_compile')
1.21,) # 'fast_run', 'fast_compile')
optdb.register('stabilize', gof.EquilibriumDB(), # replace unstable subgraphs
# replace unstable subgraphs
optdb.register('stabilize', gof.EquilibriumDB(),
1.5, 'fast_run')
optdb.register('Print1.51', PrintCurrentEnv('Post-stabilize'),
1.51,) #'fast_run', 'fast_compile')
optdb.register('specialize', gof.EquilibriumDB(), # misc special cases for speed
1.51,) # 'fast_run', 'fast_compile')
# misc special cases for speed
optdb.register('specialize', gof.EquilibriumDB(),
2, 'fast_run')
optdb.register('Print2.01', PrintCurrentEnv('Post-specialize'),
2.01, )#'fast_run', 'fast_compile')
optdb.register('uncanonicalize', gof.EquilibriumDB(),# misc special cases for speed that break canonicalization
2.01,) # 'fast_run', 'fast_compile')
# misc special cases for speed that break canonicalization
optdb.register('uncanonicalize', gof.EquilibriumDB(),
3, 'fast_run')
optdb.register('specialize_device', gof.EquilibriumDB(), # misc special cases for speed that are dependent on the device.
48.6, 'fast_run')#must be after gpu stuff at 48.5
optdb.register('merge2', gof.MergeOptimizer(), # especially constant merge
# misc special cases for speed that are dependent on the device.
optdb.register('specialize_device', gof.EquilibriumDB(),
48.6, 'fast_run') # must be after gpu stuff at 48.5
# especially constant merge
optdb.register('merge2', gof.MergeOptimizer(),
49, 'fast_run')
optdb.register('add_destroy_handler', AddDestroyHandler(),
49.5, 'fast_run', 'inplace')
optdb.register('merge3', gof.MergeOptimizer(), # final pass just to make sure
# final pass just to make sure
optdb.register('merge3', gof.MergeOptimizer(),
100, 'fast_run')
......@@ -251,12 +292,15 @@ class Mode(object):
if optimizer is None:
optimizer = config.optimizer
self.__setstate__((linker, optimizer))
#self.provided_optimizer - typically the `optimizer` arg. But if the `optimizer` arg is
# keyword corresponding to a predefined Query, then this stores the query
#self._optimizer - typically same as provided_optimizer??
#self.__get_optimizer - returns self._optimizer (possibly querying optdb with self._optimizer)
#self.optimizer - property that returns __get_optimizer()
# self.provided_optimizer - typically the `optimizer` arg.
# But if the `optimizer` arg is keyword corresponding to a predefined
# Query, then this stores the query
# self._optimizer - typically same as provided_optimizer??
# self.__get_optimizer - returns self._optimizer (possibly querying
# optdb with self._optimizer)
# self.optimizer - property that returns __get_optimizer()
def __getstate__(self):
return (self.provided_linker, self.provided_optimizer)
......@@ -275,12 +319,13 @@ class Mode(object):
self._optimizer = optimizer
self.call_time = 0
self.fn_time = 0
linker.mode = self #TODO: WHY IS THIS HERE?
linker.mode = self # TODO: WHY IS THIS HERE?
self.optimizer_time = 0
self.linker_time = 0
def __str__(self):
return "Mode(linker = %s, optimizer = %s)" % (self.provided_linker, self.provided_optimizer)
return "Mode(linker = %s, optimizer = %s)" % (
self.provided_linker, self.provided_optimizer)
def __get_optimizer(self):
if isinstance(self._optimizer, gof.Query):
......@@ -298,17 +343,20 @@ class Mode(object):
return (linker, optimizer)
def including(self, *tags):
link, opt = self.get_linker_optimizer(self.provided_linker, self.provided_optimizer)
link, opt = self.get_linker_optimizer(self.provided_linker,
self.provided_optimizer)
#N.B. opt might be a Query instance, not sure what else it might be...
# string? Optimizer? OptDB? who knows???
return self.__class__(linker=link, optimizer=opt.including(*tags))
def excluding(self, *tags):
link, opt = self.get_linker_optimizer(self.provided_linker, self.provided_optimizer)
link, opt = self.get_linker_optimizer(self.provided_linker,
self.provided_optimizer)
return self.__class__(linker=link, optimizer=opt.excluding(*tags))
def requiring(self, *tags):
link, opt = self.get_linker_optimizer(self.provided_linker, self.provided_optimizer)
link, opt = self.get_linker_optimizer(self.provided_linker,
self.provided_optimizer)
return self.__class__(linker=link, optimizer=opt.requiring(*tags))
# If a string is passed as the mode argument in function or
......@@ -321,20 +369,22 @@ predefined_modes = {'FAST_COMPILE': FAST_COMPILE,
'FAST_RUN': FAST_RUN,
}
instanciated_default_mode=None
instanciated_default_mode = None
def get_mode(orig_string):
if orig_string is None:
string = config.mode
else:
string = orig_string
if not isinstance(string, basestring):
return string #it is hopefully already a mode...
return string # it is hopefully already a mode...
global instanciated_default_mode
# The default mode is cached. However, config.mode can change
# If instanciated_default_mode has the right class, use it.
if orig_string is None and instanciated_default_mode:
if predefined_modes.has_key(string):
if string in predefined_modes:
default_mode_class = predefined_modes[string].__class__.__name__
else:
default_mode_class = string
......@@ -342,7 +392,7 @@ def get_mode(orig_string):
default_mode_class):
return instanciated_default_mode
if string in ['Mode','ProfileMode','DebugMode']:
if string in ['Mode', 'ProfileMode', 'DebugMode']:
if string == 'DebugMode':
#need to import later to break circular dependency.
from debugmode import DebugMode
......@@ -350,12 +400,13 @@ def get_mode(orig_string):
ret = DebugMode(optimizer=config.optimizer)
else:
# The import is needed in case string is ProfileMode
from profilemode import ProfileMode,prof_mode_instance_to_print
ret = eval(string+'(linker=config.linker, optimizer=config.optimizer)')
elif predefined_modes.has_key(string):
from profilemode import ProfileMode, prof_mode_instance_to_print
ret = eval(string
+ '(linker=config.linker, optimizer=config.optimizer)')
elif string in predefined_modes:
ret = predefined_modes[string]
else:
raise Exception("No predefined mode exist for string: %s"%string)
raise Exception("No predefined mode exist for string: %s" % string)
if orig_string is None:
# Build and cache the default mode
......@@ -374,12 +425,14 @@ def get_mode(orig_string):
return ret
def get_default_mode():
return get_mode(None)
# Removed: use config.mode instead.
#default_mode = config.mode
def register_mode(name, mode):
"""Add a `Mode` which can be referred to by `name` in `function`."""
if name in predefined_modes:
......
theano/tensor/opt.py
浏览文件 @ c066b30a
......@@ -1823,7 +1823,6 @@ def local_subtensor_merge(node):
merged_slices.append(slice1)
pos_1 += 1
if pos_2 < len(slices2):
merged_slices += slices2[pos_2:]
else:
......
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